Technology Research, Education, and Opinion (TREO) Talk SessionsCopyright (c) 2019 Association for Information Systems All rights reserved.https://aisel.aisnet.org/amcis2019/treo/treos
Recent Events in Technology Research, Education, and Opinion (TREO) Talk Sessionsen-usFri, 13 Sep 2019 11:57:50 PDT3600Digital Marketing in the Artificial Intelligence and Machine Learning Agehttps://aisel.aisnet.org/amcis2019/treo/treos/96
https://aisel.aisnet.org/amcis2019/treo/treos/96
We are living in a period of profound change driven by digitization, information and communication technology, machine learning, robotics, and artificial intelligence (AI) (Gupta, Keen, Shah, & Verdier, 2017). Traditional marketing is shifting to digital marketing enabled by AI and machine learning. Customer consumption behavior has changed from traditional in-store shopping to online shopping (T. Thiraviyam, 2018). U.S. Census Bureau Figures show that over the last two decades, U.S. online retail sales have grown from 5 million in 1998 to 389 million in 2016. In Europe, Enterprises Total Turnover from E-commerce increases from 15% in 2014 to 19% in 2017 (Eurostat, 2019). This research will focus on AI and machine learning effect on digital marketing and customer behavior. This research involves both interview and survey. This qualitative study will examine how marketers are capitalizing on the capabilities of AI and machine learning to predict customer behavior, offer one-to-one digital marketing, enhance sales, and increase customer satisfaction. Interviews will be conducted with executives from digital marketing companies and traditional brick and mortar companies that are embracing digital marketing. The survey will be used in these companies to capture data from digital marketing and sales personnel.
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Zhihui Ruan et al.Identifying Mortality Related Cliques in a Comorbidity Networkhttps://aisel.aisnet.org/amcis2019/treo/treos/95
https://aisel.aisnet.org/amcis2019/treo/treos/95
A trap is defined as a situation where the entities in that trap are highly likely to experience an outcome. For example, a customer who has bought a certain group of items may be designated a high potential or high risk customer on some other attribute, going beyond the market basket analysis. The purpose of this paper is to detect traps related to a problem outcome by adapting the clique property of a network. We present a heuristics based method to first develop a latent network from the transactional data and then identify outcome related traps in the form of cliques. The method is demonstrated to detect mortality related traps of diseases in patients. We applied a network approach to create relationship between diagnoses and then used the clique property to identify high-risk traps of diagnoses. Using half of the patient records, the algorithm identified mortality related cliques in the network where the mortality rate in the patients diagnosed with all diseases is significantly higher than the rate in patients without all diagnoses in a clique. We validated the results on the other half of the patient records. The presence of the clique diagnoses in the patients can help physicians take preemptive treatment decisions to avoid letting a patient “fall into a trap” of the multiple diseases. The methodology can also be applied in other problems to find contextual traps.
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Pankush Kalgotra et al.Open Government Data: From Transparency to Social Participationhttps://aisel.aisnet.org/amcis2019/treo/treos/94
https://aisel.aisnet.org/amcis2019/treo/treos/94
Increasingly the governments churn out enormous quantities of data and information, the modern information and communication technologies enable new opportunities for the citizens to manipulate, use, reuse and share the data in innovative ways. Even though important role and the potential benefits Open Government Data (OGD) can generate for the society, there are major challenges and barriers to be overcome in order to promote an ecosystem of OGD with effective social participation. The OGD is based on open government, and follows the principles: collaboration, transparency and participation. In general, the ODG practices of several countries are limited to simply releasing volumes of data in a portal without information on why and how they are collected, organized and can be used leaves citizens with herculean tasks to determine their relevance and reliability. The ODG ecosystem of the Brazilian federal government is an example of this scenario, which has portals with the objective of speeding up information release efforts and only making the data accessible. Expected that open and transparent governments are more accountable to their population and less corrupt. The current direction of scientific research indicates that the OGD to seek advances in: government transparency, increased social participation, more efficient sustainable cities with social participation in management and governance. So studies point out that only access to data is not enough it is necessary, modern platforms that allow effective social participation in a collaborative structure and empowering society and civil servants to develop a new ecosystem for OGD. Thus there are two major streams of OGD studies that address these gaps, a research aspect on the publication, use and reuse of open data for innovation purposes, and another that establishes research focused on effective social participation in the OGD ecosystem the publication, it is noted that efforts are needed to integrate these two streams. In this proposal, we will seek to present discussions and solutions on how these two great streams can be developed together addressing transparency for innovation goals, and addressing issues of social participation from the development of new policies for OGD and portals. Thus, we will explain the context and address opportunities, challenges and suggestions.
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Dyego Alves Silva et al.Properly Defining the Sharing Economyhttps://aisel.aisnet.org/amcis2019/treo/treos/93
https://aisel.aisnet.org/amcis2019/treo/treos/93
To completely understand a phenomenon we must first define it; unfortunately, there is not one agreed upon definition of “Sharing Economy.” In addition, there are at least 17 different terms referring to the Sharing Economy (Dredge and Gyimóthy 2015), while a preliminary literature review uncovered 48 different definitions of “sharing economy” alone. The dictionary definition of sharing economy is “economic activity that involves individuals buying or selling usually temporary access to goods or services especially as arranged through an online company or organization” (“Sharing Economy | Definition of Sharing Economy by Merriam-Webster” 2017). Sundararajan (2016) prefers use “Access Economy,” describing it as “the value in taking underutilized assets and making them accessible to a community, leading to a reduced need for ownership of those assets” (Sundararajan 2016, p. 30). Some prefer “Collaborative Consumption,” defined as “the peer-to-peer-based activity of obtaining, giving, or sharing access to goods and services, coordinated through community-based online services” (Hamari 2013, p. 3). Less used, is the term “Access-Based Consumption,” defined as “people coordinating the acquisition or distribution of a resource for a fee or other compensation” (Barnes and Mattsson 2017, p. 282). An even simpler definition is given to the term “Access Economy,” defined as “provides temporary access to consumption resources for a fee or for free without transfer of ownership” (Eckhardt and Bardhi 2016, p. 210). With so many terms and definitions of the same phenomenon, there is an opportunity to develop one that is all-encompassing, which would help develop proper boundaries for the phenomenon. We propose to do this using textual analysis on the definitions in the most cited publications and books.
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Eric VillafrancaTaxonomy of Misinformation Harms from Social Media in Humanitarian Criseshttps://aisel.aisnet.org/amcis2019/treo/treos/92
https://aisel.aisnet.org/amcis2019/treo/treos/92
During humanitarian crises, people face dangers and need a large amount of information in a short period of time. Such need creates the base for misinformation such as rumors, fake news or hoaxes to spread within and outside the affected community. It could be unintended misinformation with unconfirmed details, or intentional disinformation created to trick people for benefits. Information harms are its effects that can generate serious short term or long-term consequences. Although some researchers have created misinformation detection systems and algorithms, or examined the roles of behavioral characteristics of involved parties, or examined the way successful rumors spread and convince people, not much attention has been paid regarding the types of misinformation harms. Adopting the findings from the literature, in the humanitarian crises, we propose a taxonomy of information harms that can be used in the context of humanitarian crises. Such taxonomy can act as the base for future research to quantitatively measure the harms in specific contexts.
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Thi Tran et al.Maximizing the Performance of Agile Teams for IoT Developmenthttps://aisel.aisnet.org/amcis2019/treo/treos/91
https://aisel.aisnet.org/amcis2019/treo/treos/91
Agile software development is a popular approach which focuses on creating small working pieces of software in iterations. One of its major benefits is that it allows customers to provide feedback and change requirements during the development phase. This can lead to outcomes that better match their specifications, which can help save time and money when compared to traditional approaches, such as plan-driven development. In today’s fast-paced world, the ability to cope with continuous changes has become vital for organizations to survive, which is one of the reasons agile software development has gained more popularity. Multiple agile methodologies exist, each consisting of shared and unique practices that can be thought of as different ways of working. Organizations are not restricted to choosing just one agile methodology or adopting all of its practices, rather they can combine practices from different methodologies. This allows organization to select those practices that suit their specific needs. Another new paradigm is the Internet of Things (IoT), which is emerging as one of the largest technological industry segments worldwide. With the IoT market growing and agile software development gaining popularity, it is important to research how agile software development can be leveraged in IoT development. This is important, because IoT development has certain characteristics that differ from other software development. For instance, IoT combines both hardware and software, whereas non-IoT applications focus mainly on software. In addition, IoT solutions are very cloud-centric and often have additional security and privacy challenges. These unique requirements impact the teams developing IoT solutions. Therefore, the objective of this research is to determine how the performance of an agile team in IoT development can be maximized. This is a mixed methods study consisting of a survey and a semi-structured interview. Participants will be selected who are working in agile teams at IoT development companies with under 50 employees. After considering all existing agile practices, a selection has been made of 15 agile practices and 9 agile engineering practices that are used by the majority of agile teams. A 7-point Likert scale survey will be employed to ask participants how important these most commonly used agile (engineering) practices are for their team. In addition, a set of IT skills has been defined, which includes skills such as programming, systems design, project management and others. Participants will be asked about the skills that their team performs best at, to determine if there is a correlation between the skills that are present in teams and the agile practices the team uses. In a follow-up semi-structured interview, participants will be asked how the agile practices they identified as most important contribute to the success of their team. The results will help determine if there is a correlation between the agile practices and skills in teams, and their success. This study will provide companies active in IoT development insight into the (combinations of) agile practices that lead to success.
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Wouter Moedt et al.Legitimization of Information Security Policies in Organizationshttps://aisel.aisnet.org/amcis2019/treo/treos/90
https://aisel.aisnet.org/amcis2019/treo/treos/90
We argue that most organizations fail to internalize information security policies (ISPs) and only ceremonially adopt them because the adoption decision is generally driven by external legitimization purposes rather than efficiency gains. Based on the data collected from semi-structured interviews of senior executives, our preliminary findings reveal that ISPs are not integrated to the existing organizational routines until there is an external jolt such as a security breach. However, given the sudden nature of these jolts, ISPs do not gain internal legitimacy. We propose that after the implementation and before the internalization of ISPs, organizations need to actively integrate ISPs into their existing routines, with the aim of internal legitimization in the eyes of the organizational members.
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Alper Yayla et al.How Does Bryan’s Online Behavior Impact His Privacy Risk Exposure?https://aisel.aisnet.org/amcis2019/treo/treos/89
https://aisel.aisnet.org/amcis2019/treo/treos/89
Behavioral privacy research has primarily focused on consumers with privacy concern. However, a common refrain in public discourse on online tracking of an Internet user’s browsing activity is “I’ve got nothing to hide,” and thus “have nothing to fear” from such tracking. One prospective explanation for the “nothing to hide” (NtH) view is these Internet users may lack awareness of how online tracking may affect them. In general, more research is needed on defining and illustrating online privacy risk for Internet users so that they can make more informed decisions on privacy risk management. Therefore, the present study conducts an experiment to illustrate online tracking and its potential effects. Secondly, the experiment examines the effectiveness of privacy enhancing technology (PET) to reduce online tracking and its effects. As a means to provide scope and context, data collection of online browsing is facilitated using a persona; i.e., a fictitious representation of a realistic person. A persona typically captures demographics, technology usage, personality traits, and is typically given a name and often a picture. Personas are commonly used in HCI work as part of system design or user experience analysis for a given system. More recently, personas have been used to facilitate privacy risk and security threat analyses. The fictitious NtH persona defined for the present research includes a name (e.g., “Bryan”), photo, age, marital status, career, hobbies, technology usage, and “something” to hide. Given Bryan’s NtH view on online tracking, he does not use any PET while browsing online. Based on Bryan’s characteristics, an online browsing script is constructed to simulate the types of web sites that a person like Bryan might visit and the searches he might make. Software is used to collect third-party tracking domain names affiliated with each web page he visits. In addition, the full (i.e., descriptive) URLs are collected per page visited. Given the third-party trackers and full URLs per web page associated with Bryan’s online browsing, analysis is performed on how much information tracking companies can glean about Bryan. In particular, an inventory of full URLs will be provided to study participants who are not part of the research team. These participants will attempt to infer as much about Bryan’s demographics, career, hobbies, and his “something to hide” as possible. Secondly, the participants will be asked to make various inferences about Bryan based on his online browsing behavior that may have financial or other consequences. A second set of browsing data will be captured using a PET (e.g., a browser plug-in that blocks tracking). A similar list of online trackers and full URLs per site visited will be captured, followed by similar analysis of inferences made on Bryan. It is expected that Bryan will encounter significantly less trackers, and thus, fewer characteristics may be inferred about him when using a PET. Output from analyzing Bryan’s online tracking, inferences that may be made, and the degree of PET effectiveness in blocking tracking/inferences will serve as input into vignettes that illustrate privacy risk and the impact of managing such risk. These vignettes will subsequently be used in a survey instrument to test behavioral theory on privacy risk management.
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Janine SpearsDoes Marxism Still Apply? Exploring Digital Worker Perspectives in the Sharing Economyhttps://aisel.aisnet.org/amcis2019/treo/treos/88
https://aisel.aisnet.org/amcis2019/treo/treos/88
Imagine a world full of people that own nothing but have access to everything they need because they share things such as tools, meals, rides, couches, and even homes. While this may sound utopian, we are seeing a glimpse of what this society would look like with the rise of the sharing economy- a hybrid economy, characterized by sharing as well as commercial exchange (Lessig 2008). The sharing economy has created new opportunities for digital labor. Sharing firms such as Task Rabbit and Amazon’s Mechanical Turk (MTurk) match those who need to complete tasks with others that have the time and knowledge to complete those tasks online (Brinkley 2016). The benefit to workers comes in the form of new work opportunities, empowerment, schedule flexibility, and social benefits. However, the disadvantage to workers comes in the form of very few substantive rights and benefits, and low wages. While the sharing economy phenomenon has been gaining traction in the literature, we want to understand the phenomenon from a labor perspective. Specifically, we have conducted a preliminary literature review of labor in the sharing economy, and the results show that few studies (3 of 30 in our sample) focus on the perspective of the worker. We feel that this makes for an incomplete understanding of the phenomenon. We propose to study the perspectives of digital workers in the sharing economy using an exploratory qualitative method (i.e. grounded theory) with open-ended questions. We will use MTurk as a primary data source, and we will triangulate the results with excerpts from digital worker blog sites and popular media. While Deng et al. (2016) viewed the phenomenon through a value sensitive design lens, we will use a Marxist lens to answer the following research question: How can the Marxist perspective inform our understanding of digital work in the sharing economy? Our goal is to determine if the Marxist exploitation ideology holds in the context of the sharing economy.
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Eric VillafrancaAMCIS 2019 Cancun: TICómetro. Digital Skills Students Assessment at UNAMhttps://aisel.aisnet.org/amcis2019/treo/treos/87
https://aisel.aisnet.org/amcis2019/treo/treos/87
In this document I present the TICómetro, an instrument to evaluate access and use of Information and Communication Technologies of students in High School at National Autonomous University of Mexico. The TICómetro is a diagnostic evaluation instrument that provides information about how much access has students to ICT, it means Internet access at home and number and kind of electronic devices. Likewise, information about how students can use technology in four dimensions: Information processing; search, selection and evaluation of digital information; security and collaboration and communication through digital tools. TICómetro development was founded on international standards like ICDL and ISTE. We considered other sources like research results and national policies in digital education (Chile matrix of digital skills). This diagnostic is an online test, created on MOODLE platform using questionnaire module. Questions are multiple choice type, a problem which requires knowledge and doing skills to solve them. Other questions are denominated “answer construction”, a problem and a series of images or phrases that the student must put in order to show that he knows how to execute a procedure, or point into an image to demonstrate knowing about software interface. Finally, we have developed three simulation question type for MOODLE, to present real situations to solve problems related to text processor, spreadsheet and Internet search. Assessment population is about 33,000 students each year. So, we have results of seven generations of high school students which allows us to affirm that young people are not digital natives. They have educational needs about using technology, especially in regard to the use of ICT for learning.
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Marina Kriscautzky-Laxague